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Research On Workshop Scheduling Problem Based On Artificial Intelligence Algorithm

Posted on:2021-03-19Degree:MasterType:Thesis
Country:ChinaCandidate:Y QuFull Text:PDF
GTID:2392330647453015Subject:Marine Engineering
Abstract/Summary:PDF Full Text Request
With the increasing attention on the manufacturing industry,"made in China 2025" has become a high-profile new word.Intelligent production scheduling management department,next to the production department,is a crucial part of intelligent manufacturing.In this paper,the research significance of intelligent manufacturing is expounded from the perspective of automation and digitization by analyzing the domestic and foreign status of intelligent manufacturing.In this paper,the scheduling problem of production workshop with different constraint conditions is analyzed,and the scheduling problem of flexible job workshop with processing sequence requirement and mixed pipeline workshop with parallel machine is deeply studied by establishing mathematical modeling.Firstly,based on the improved genetic annealing algorithm,the flexible job shop scheduling problem is analyzed and studied,and the production inventory and resources are combined to make the production scientific.According to the production demand and inventory to adjust the proportion of raw materials and operation quantity,so as to realize the combination of upper management and lower intelligent production.In this paper,a mathematical model is established to simulate the production scheduling of enterprises under certain constraints,including different production requirements of each raw material and different sequence requirements between sections.Then,an improved genetic annealing algorithm is designed to optimize the production.Secondly,based on the artificial swarm algorithm,this paper analyzes and studies the scheduling problem of mixed pipeline workshop with parallel machine,and establishes the relationship between inventory and production by introducing the concept of batch.Through mathematical modeling to simulate the production situation,artificial colony algorithm design,multi-dimensional search relative global optimal solution,the final realization of intelligent production scheduling.Finally through Visual Studio2017 development platform,using c + + language to achieve improved genetic annealing algorithm instance of flexible job shop scheduling and simulation,using c # language to realize artificial colony algorithm of mixed assembly line shop scheduling problem with parallel machines instance simulation,looking for does not affect the algorithm efficiency and can produce high quality solutions for parameter setting,prove the quality and efficiency of the algorithm.
Keywords/Search Tags:Intelligent scheduling, production scheduling, artificial bee colony algorithm, genetic annealing algorithm, parallel machine
PDF Full Text Request
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